scholarly journals A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

2021 ◽  
Author(s):  
Delin Sun ◽  
Gopalkumar Rakesh ◽  
Emily K. Clarke-Rubright ◽  
Courtney C. Haswell ◽  
Mark Logue ◽  
...  
Keyword(s):  
Cortical Thickness ◽  
Statistical Power ◽  
Additive Model ◽  
Case Control ◽  
Test Case ◽  
Site Specific ◽  
P Values ◽  
Age Related ◽  
Significant Case ◽  
The Impact

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,343 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,067 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM were more sensitive to the detection of significant case-control differences in regional cortical thickness (Chi2(3) = 34.339, p < 0.001), and case-control differences in age-related cortical thinning (Chi2(3) = 15.128, p = 0.002). Specifically, ComBat-GAM led to larger effect size estimates of cortical thickness reductions (corrected p-values < 0.001), smaller age-appropriate declines (corrected p-values < 0.001), and lower female to male contrast (corrected p-values < 0.001) in cases compared to controls relative to other harmonization methods. Harmonization with ComBat-GAM also led to greater estimates of age-related declines in cortical thickness (corrected p-values < 0.001) in both cases and controls compared to other harmonization methods. Our results support the use of ComBat-GAM for harmonizing cortical thickness data aggregated from multiple sites and scanners to minimize confounds and increase statistical power.

scholarly journals Model Averaging with AIC Weights for Hypothesis Testing of Hormesis at Low Doses

Dose-Response ◽  
2017 ◽  
Vol 15 (2) ◽  
pp. 155932581771531
Author(s):  
Steven B. Kim ◽  
Nathan Sanders
Keyword(s):  
Hypothesis Testing ◽  
Dose Response ◽  
Statistical Power ◽  
Parametric Model ◽  
Semiparametric Models ◽  
Parametric Models ◽  
Large Sample Size ◽  
Low Doses ◽  
P Values ◽  
The Impact

For many dose–response studies, large samples are not available. Particularly, when the outcome of interest is binary rather than continuous, a large sample size is required to provide evidence for hormesis at low doses. In a small or moderate sample, we can gain statistical power by the use of a parametric model. It is an efficient approach when it is correctly specified, but it can be misleading otherwise. This research is motivated by the fact that data points at high experimental doses have too much contribution in the hypothesis testing when a parametric model is misspecified. In dose–response analyses, to account for model uncertainty and to reduce the impact of model misspecification, averaging multiple models have been widely discussed in the literature. In this article, we propose to average semiparametric models when we test for hormesis at low doses. We show the different characteristics of averaging parametric models and averaging semiparametric models by simulation. We apply the proposed method to real data, and we show that P values from averaged semiparametric models are more credible than P values from averaged parametric methods. When the true dose–response relationship does not follow a parametric assumption, the proposed method can be an alternative robust approach.

scholarly journals A normative modelling approach reveals age-atypical cortical thickness in a subgroup of males with autism spectrum disorder

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Richard A. I. Bethlehem ◽  
Jakob Seidlitz ◽  
Rafael Romero-Garcia ◽  
Stavros Trakoshis ◽  
Guillaume Dumas ◽  
...  
Keyword(s):  
Cortical Thickness ◽  
Autism Spectrum ◽  
Case Control ◽  
Small Subset ◽  
Typically Developing ◽  
Average Case ◽  
Age Related ◽  
Small Subgroup ◽  
Individualized Approach ◽  
Age Range

AbstractUnderstanding heterogeneity is an important goal on the path to precision medicine for autism spectrum disorders (ASD). We examined how cortical thickness (CT) in ASD can be parameterized as an individualized metric of atypicality relative to typically-developing (TD) age-related norms. Across a large sample (n = 870 per group) and wide age range (5–40 years), we applied normative modelling resulting in individualized whole-brain maps of age-related CT atypicality in ASD and isolating a small subgroup with highly age-atypical CT. Age-normed CT scores also highlights on-average differentiation, and associations with behavioural symptomatology that is separate from insights gleaned from traditional case-control approaches. This work showcases an individualized approach for understanding ASD heterogeneity that could potentially further prioritize work on a subset of individuals with cortical pathophysiology represented in age-related CT atypicality. Only a small subset of ASD individuals are actually highly atypical relative to age-norms. driving small on-average case-control differences.

scholarly journals The impact of non-additive genetic associations on age-related complex diseases

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Marta Guindo-Martínez ◽  
◽  
Ramon Amela ◽  
Silvia Bonàs-Guarch ◽  
Montserrat Puiggròs ◽  
...  
Keyword(s):  
X Chromosome ◽  
Additive Model ◽  
Complex Diseases ◽  
Additive Models ◽  
Genotype Imputation ◽  
Reference Panel ◽  
Genome Wide Association Studies ◽  
Age Related ◽  
Genome Wide ◽  
The Impact

AbstractGenome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.

scholarly journals The impact of non-additive genetic associations on age-related complex diseases

2020 ◽  
Author(s):  
Marta Guindo-Martínez ◽  
Ramon Amela ◽  
Silvia Bonàs-Guarch ◽  
Montserrat Puiggròs ◽  
Cecilia Salvoro ◽  
...  
Keyword(s):  
X Chromosome ◽  
Additive Model ◽  
Complex Diseases ◽  
Additive Models ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Age Related ◽  
Genome Wide ◽  
New Findings ◽  
The Impact

AbstractGenome-wide association studies (GWAS) are not fully comprehensive as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implemented an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels, includes the analysis of the X chromosome and non-additive models to test for association. We applied this methodology to 62,281 subjects across 22 age-related diseases and identified 94 genome-wide associated loci, including 26 previously unreported. We observed that 27.6% of the 94 loci would be missed if we only used standard imputation strategies and only tested the additive model. Among the new findings, we identified three novel low-frequency recessive variants with odds ratios larger than 4, which would need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.

scholarly journals Number of incident cases of the main eye diseases of ageing in the UK Biobank cohort, projected over a 25-year period from time of recruitment

2018 ◽  
Vol 102 (11) ◽  
pp. 1533-1537 ◽  
Author(s):  
Parul Desai ◽  
Darwin C Minassian ◽  
Angela Reidy ◽  
Naomi Allen ◽  
Cathie Sudlow
Keyword(s):  
Macular Degeneration ◽  
Statistical Power ◽  
Case Control ◽  
Age Related Macular Degeneration ◽  
Eye Disease ◽  
Uk Biobank ◽  
Case Control Studies ◽  
Age Related ◽  
The Uk ◽  
Nested Case Control

ObjectivesTo estimate the number of new cases of age-related macular degeneration, cataract and glaucoma accruing in the UK Biobank cohort, over a period of 25 years from time of recruitment. Our secondary objective was to assess the statistical power of nested case–control studies of these eye diseases. We aimed to provide quantitative information relevant to UK Biobank’s eye disease case ascertainment efforts and to the potential for UK Biobank-based research into the causes of eye disease.MethodsWe constructed a Markov discrete-time state transition model to simulate the population dynamics of the eye disorders within the UK Biobank cohort, using prevalence data from population-based epidemiological studies to derive incidence, and Office for National Statistics data on mortality and migration overseas.ResultsBy 2023, >900 new cases of each of ‘wet’ (neovascular) and ‘dry’ age-related macular degeneration, >1200 cases of primary open angle glaucoma and almost 15 000 cases of cataracts are expected to have accrued in the subcohort of 68 500 participants who had ocular assessment at baseline, with around seven times as many cases of each disease in the whole cohort of 500 000 participants. These predicted incident case numbers generate good or substantial statistical power for a range of nested case–control studies of potential genetic, lifestyle and environmental determinants of disease.ConclusionsOver the next few years, UK Biobank is expected to generate sufficient numbers of new cases for statistically well-powered studies of the determinants of the major causes of sight loss: age-related macular degeneration, vision-impairing cataract and glaucoma.

scholarly journals Association versus Prediction: the impact of cortical surface smoothing and parcellation on brain age

2020 ◽  
Author(s):  
Yashar Zeighami ◽  
Alan C. Evans
Keyword(s):  
Cortical Thickness ◽  
Prediction Accuracy ◽  
Negative Relationship ◽  
Correct Choice ◽  
Age Related ◽  
Smoothing Effects ◽  
The Impact ◽  
The Relationship ◽  
Brain Age ◽  
Age Prediction

AbstractAssociation and prediction studies of the brain target the biological consequences of aging and their impact on brain function. Such studies are conducted using different smoothing levels and parcellations at the preprocessing stage, on which their results are dependent. However, the impact of these parameters on the relationship between association values and prediction accuracy is not established. In this study, we used cortical thickness and its relationship with age to investigate how different smoothing and parcellation levels affect the detection of age-related brain correlates as well as brain age prediction accuracy. Our main measures were resel numbers - resolution elements - and age-related variance explained. Using these common measures enabled us to directly compare parcellation and smoothing effects in both association and prediction studies. In our sample of N=608 participants with age range 18-88, we evaluated age-related cortical thickness changes as well as brain age prediction. We found a negative relationship between prediction performance and correlation values for both parameters. Our results also quantify the relationship between delta age estimates obtained based on different processing parameters. Furthermore, with the direct comparison of the two approaches, we highlight the importance of correct choice of smoothing and parcellation parameters in each task, and how they can affect the results of the analysis in opposite directions.

scholarly journals Combined effects of age and BMI are related to altered cortical thickness in adolescence and adulthood

2019 ◽  
Author(s):  
Margaret L. Westwater ◽  
Raquel Vilar-López ◽  
Hisham Ziauddeen ◽  
Antonio Verdejo-García ◽  
Paul C. Fletcher
Keyword(s):  
Cortical Thickness ◽  
Inferior Frontal Gyrus ◽  
Age Groups ◽  
Overweight And Obesity ◽  
Adult Brain ◽  
Age Related ◽  
Adolescents And Adults ◽  
The Right ◽  
The Impact ◽  
The Relationship

AbstractOverweight and obesity are associated with functional and structural alterations in the brain, but how these associations change across critical developmental periods remains unknown. Here, we examined the relationship between age, body mass index (BMI) and cortical thickness (CT) in healthy adolescents (n=70; 14 – 19 y) and adults (n=75; 25 – 45 y). We also examined the relationship between adiposity, impulsivity, measured by delay discounting (DD), and CT of the inferior frontal gyrus (IFG), a region key to impulse control. A significant age-by-BMI interaction was observed in both adolescents and adults; however, the direction of this relationship differed between age groups. In adolescents, increased age-adjusted BMI Z-score attenuated age-related thinning globally and in the right superior frontal gyrus. In adults, increased BMI augmented age-related CT reductions, both globally and in bilateral parietal cortex. Although DD was unrelated to adiposity in both groups, increased DD and BMI were both associated with reduced IFG thickness in adults. Our findings suggest that the known age-related changes in CT in adolescence and adulthood are altered by adiposity. The impact of weight on cortical development and its functional implications would suggest that future studies of adolescent and adult brain development take adiposity into account.

The Impact of Bioconjugation on the Interfacial Activity of a Protein Biosurfactant

2018 ◽  
Author(s):  
Hossam H Tayeb ◽  
Marina Stienecker ◽  
Anton Middelberg ◽  
Frank Sainsbury
Keyword(s):  
Polyethylene Glycol ◽  
Colloidal Stability ◽  
Point Mutations ◽  
Pharmaceutical Formulations ◽  
Industrial Processes ◽  
Parent Molecule ◽  
Site Specific ◽  
Interfacial Activity ◽  
Surface Active ◽  
The Impact

Biosurfactants, are surface active molecules that can be produced by renewable, industrially scalable biologic processes. DAMP4, a designer biosurfactant, enables the modification of interfaces via genetic or chemical fusion to functional moieties. However, bioconjugation of addressable amines introduces heterogeneity that limits the precision of functionalization as well as the resolution of interfacial characterization. Here we designed DAMP4 variants with cysteine point mutations to allow for site-specific bioconjugation. The DAMP4 variants were shown to retain the structural stability and interfacial activity characteristic of the parent molecule, while permitting efficient and specific conjugation of polyethylene glycol (PEG). PEGylation results in a considerable reduction on the interfacial activity of both single and double mutants. Comparison of conjugates with one or two conjugation sites shows that both the number of conjugates as well as the mass of conjugated material impacts the interfacial activity of DAMP4. As a result, the ability of DAMP4 variants with multiple PEG conjugates to impart colloidal stability on peptide-stabilized emulsions is reduced. We suggest that this is due to constraints on the structure of amphiphilic helices at the interface. Specific and efficient bioconjugation permits the exploration and investigation of the interfacial properties of designer protein biosurfactants with molecular precision. Our findings should therefore inform the design and modification of biosurfactants for their increasing use in industrial processes, and nutritional and pharmaceutical formulations.

Exploring power in response inhibition tasks using the bootstrap: The impact of number of participants, number of trials, effect magnitude, and study design

2019 ◽  
Author(s):  
Curtis David Von Gunten ◽  
Bruce D Bartholow
Keyword(s):  
Study Design ◽  
Effect Size ◽  
Statistical Power ◽  
Bootstrap Sampling ◽  
Reliable Measure ◽  
Internal Reliability ◽  
The Impact ◽  
Power Analyses ◽  
Effect Magnitude

A primary psychometric concern with laboratory-based inhibition tasks has been their reliability. However, a reliable measure may not be necessary or sufficient for reliably detecting effects (statistical power). The current study used a bootstrap sampling approach to systematically examine how the number of participants, the number of trials, the magnitude of an effect, and study design (between- vs. within-subject) jointly contribute to power in five commonly used inhibition tasks. The results demonstrate the shortcomings of relying solely on measurement reliability when determining the number of trials to use in an inhibition task: high internal reliability can be accompanied with low power and low reliability can be accompanied with high power. For instance, adding additional trials once sufficient reliability has been reached can result in large gains in power. The dissociation between reliability and power was particularly apparent in between-subject designs where the number of participants contributed greatly to power but little to reliability, and where the number of trials contributed greatly to reliability but only modestly (depending on the task) to power. For between-subject designs, the probability of detecting small-to-medium-sized effects with 150 participants (total) was generally less than 55%. However, effect size was positively associated with number of trials. Thus, researchers have some control over effect size and this needs to be considered when conducting power analyses using analytic methods that take such effect sizes as an argument. Results are discussed in the context of recent claims regarding the role of inhibition tasks in experimental and individual difference designs.

Sign in / Sign up

Export Citation Format

Share Document